Field of the Invention
This invention relates to high dynamic range (HDR) image processing, and in particular, it relates to automatically selecting optimum tone mapping operators and gamut mapping algorithms based on scene classification.
Description of Related Art
High dynamic range (HDR) imaging is a technique used in image processing and digital photography to handle sources that have extremely large ranges of brightness (light intensity). For example, an outdoor scene in daylight may include blue sky and sunlit objects as well as objects in shadows; a night scene may include neon lights and brightly lit objects as well as poorly lit objects; an indoor scene may include bright windows as well as darker areas, etc. These scenes pose a challenge for imaging devices such as digital cameras; the dynamic range of the image sensor of currently available digital cameras often cannot adequately image such scenes. If the exposure level is adequate for capturing details of darker areas of the scene, the brighter areas will often be overexposed with details lost; conversely, if the exposure level is adequate for capturing details of brighter areas of the scene, the darker areas will often be underexposed with details lost.
HDR imaging techniques deal with this problem by taking multiple images of the same scene at various exposure levels (referred to as exposure bracketing), and then digitally merging or combining the multiple images to create an HDR image that contains information from the original multiple images, so that details in both brighter and darker areas are adequately expressed in the HDR image. Methods for creating an HDR image from multiple images (referred to as brackets) are generally known; the process typically involves aligning the multiple images, removing ghosts in the multiple images (ghosts may appear when an object in the scene moved during the taking of the multiple images), and merging the multiple images to form the HDR image.
In order to print an HDR image by a printer, the image must first be rendered into colors supported by the printer. Typically, the range of colors that it is possible to produce on a printer, with ink or toner, is much smaller than the range contained in an HDR image. For example, an HDR image may have a dynamic range of 100,000:1 while an image for printing by a printer may have a tonal value ranging from just 1 to 255. During printing, the much greater range of colors in the HDR image must be fitted into the smaller range that it is possible to print. This conversion includes tone mapping, which converts the tonal value of an image from a high dynamic range (HDR) to a lower dynamic range (LDR), and gamut mapping, which converts the LDR image from the RGB (red, green, blue) color space to the CMYK (cyan, magenta, yellow, black) color space for printing. Various tone mapping algorithms are known.
Scene classification or image classification has been used in image processing. For example, methods for classifying scenes into indoor and outdoor scenes have been proposed.